| 书目名称 | Weak Dependence: With Examples and Applications |
| 编辑 | Jérôme Dedecker,Paul Doukhan,Clémentine Prieur |
| 视频video | |
| 概述 | Make it simple to read and thus the mathematical level needed is as low as possible.Aimed to fix the notions in the area in development.May be considered as an introduction to weak dependence.Propose |
| 丛书名称 | Lecture Notes in Statistics |
| 图书封面 |  |
| 描述 | Time series and random ?elds are main topics in modern statistical techniques. They are essential for applications where randomness plays an important role. Indeed, physical constraints mean that serious modelling cannot be done - ing only independent sequences. This is a real problem because asymptotic properties are not always known in this case. Thepresentworkisdevotedtoprovidingaframeworkforthecommonlyused time series. In order to validate the main statistics, one needs rigorous limit theorems. In the ?eld of probability theory, asymptotic behavior of sums may or may not be analogous to those of independent sequences. We are involved with this ?rst case in this book. Very sharp results have been proved for mixing processes, a notion int- duced by Murray Rosenblatt [166]. Extensive discussions of this topic may be found in his Dependence in Probability and Statistics (a monograph published by Birkhau ¨ser in 1986) and in Doukhan (1994) [61], and the sharpest results may be found in Rio (2000)[161]. However, a counterexample of a really simple non-mixing process was exhibited by Andrews (1984) [2]. The notion of weak dependence discussed here takes real account of the available m |
| 出版日期 | Book 2007 |
| 关键词 | Resampling; fitting; parametric statistics; statistics |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-0-387-69952-3 |
| isbn_softcover | 978-0-387-69951-6 |
| isbn_ebook | 978-0-387-69952-3Series ISSN 0930-0325 Series E-ISSN 2197-7186 |
| issn_series | 0930-0325 |
| copyright | Springer-Verlag New York 2007 |
发表于 2025-3-21 20:06:06
